Sensor Validation and Calibration

Abstract

Systems, methods, tangible non-transitory computer-readable media, and devices associated with radar validation and calibration are provided. For example, target positions for targets can be determined based on imaging devices. The targets can be located at respective predetermined positions relative to the imaging devices. Radar detections of the targets can be generated based on radar devices. The radar devices can be located at a predetermined position relative to the imaging devices. Filtered radar detections can be generated based on performance of filtering operations on the radar detections. A detection error can be determined for the radar devices based on calibration operations performed using the filtered radar detections and the target positions determined based on the one or more imaging devices. Furthermore, the radar devices can be calibrated based on the detection error.

1 .- 20 . (canceled) 
     
     
         21 . A computer-implemented method for cross-validating imaging devices, the method comprising:
 determining, using an imaging device, a first set of positions of a plurality of targets;   determining, using a LIDAR device, a second set of positions of the plurality of targets; and   cross-validating the first imaging device and the second imaging device based at least in part on one or more comparisons of the first set of positions to the second set of positions.   
     
     
         22 . The computer-implemented method of  claim 21 , wherein cross-validating the imaging device and the LIDAR device comprises:
 comparing the first set of positions to the second set of positions to determine a difference between the first set of positions and the second set of positions indicative of an amount of imaging error between the first imaging device and the second imaging device; and   validating the LIDAR device based at least in part on the difference between the first set of positions and the second set of positions.   
     
     
         23 . The computer-implemented method of  claim 21 , wherein cross-validating the imaging device and the LIDAR device comprises:
 comparing the first set of positions to the second set of positions to determine a difference between the first set of positions and the second set of positions indicative of an amount of imaging error between the first imaging device and the second imaging device; and   validating the imaging device based at least in part on the difference between the first set of positions and the second set of positions.   
     
     
         24 . The computer-implemented method of  claim 21 , wherein determining the first set of positions of the plurality of targets comprises:
 causing the imaging device to capture one or more images of the plurality of targets; and   determining the first set of positions of the plurality of targets based at least in part on the one or more images of the plurality of targets.   
     
     
         25 . The computer-implemented method of  claim 21 , wherein determining the second set of positions of the plurality of targets comprises:
 causing the LIDAR device to capture one or more images of the plurality of targets; and   determining the second set of positions of the plurality of targets based at least in part on the one or more images of the plurality of targets.   
     
     
         26 . The computer-implemented method of  claim 21 , wherein the first imaging device comprises a camera. 
     
     
         27 . The computer-implemented method of  claim 21 , wherein the first set of positions comprises an orientation and a distance of at least one target of the plurality of targets from the imaging device; and wherein the second set of positions comprises an orientation and a distance of the at least one target of the plurality of targets from the LIDAR device. 
     
     
         28 . The computer-implemented method of  claim 21 , wherein the plurality of targets comprises one or more fiducial images that identify a respective target of the plurality of targets and is encoded with information about the respective target. 
     
     
         29 . The computer-implemented method of  claim 21 , further comprising:
 subsequent to cross-validating the imaging device and the LIDAR device, determining, using the imaging device and the LIDAR device, a plurality of target positions of the plurality of targets; and   calibrating one or more sensors based at least in part on the plurality of target positions.   
     
     
         30 . A computing system, comprising:
 one or more processors; and   one or more non-transitory computer-readable media storing instructions that when executed by the one or more processors cause the one or more processors to perform operations comprising:
 determining, using a first imaging device, a first set of positions of a plurality of targets; 
 determining, using a second imaging device, a second set of positions of the plurality of targets; and 
 cross-validating the first imaging device and the second imaging device based at least in part on one or more comparisons of the first set of positions to the second set of positions. 
   
     
     
         31 . The computing system of  claim 30 , wherein the first imaging device has a different resolution from the second imaging device. 
     
     
         32 . The computing system of  claim 30 , wherein the first imaging device is a different type of imaging device than the second imaging device. 
     
     
         33 . The computing system of  claim 30 , wherein the first imaging device or the second imaging device is a LIDAR device. 
     
     
         34 . The computing system of  claim 33 , wherein cross-validating the first imaging device and the second imaging device comprises:
 validating the LIDAR device based at least in part on a difference between the first set of positions and the second set of positions.   
     
     
         35 . The computing system of  claim 30 , wherein the first set of positions comprises an orientation and a distance of at least one target of the plurality of targets from the first imaging device, and wherein the second set of positions comprises an orientation and a distance of at least one target of the plurality of targets from the second imaging device. 
     
     
         36 . The computing system of  claim 35 , wherein the first imaging device comprises a camera. 
     
     
         37 . The computing system of  claim 36 , wherein cross-validating the first imaging device and the second imaging device comprises:
 validating the camera based at least in part on a difference between the first set of positions and the second set of positions.   
     
     
         38 . One or more non-transitory computer-readable media storing instructions that when executed by one or more processors cause the one or more processors to perform operations comprising:
 determining, using an imaging device, a first set of positions of a plurality of targets;   determining, using a LIDAR device, a second set of positions of the plurality of targets;   determining a difference between the first set of positions and the second set of positions, wherein the difference between the first set of positions and the second set of positions is indicative of an amount of imaging error between the first imaging device and the second imaging device; and   cross-validating the first imaging device and the second imaging device based at least in part on the difference between the first set of positions and the second set of positions.   
     
     
         39 . The one or more non-transitory computer-readable media of  claim 38 , wherein the first imaging device comprises a camera and the second imaging device comprises a LiDAR device. 
     
     
         40 . The one or more non-transitory computer-readable media of  claim 38 , wherein the operations further comprise:
 subsequent to cross-validating the first imaging device and the second imaging device, determining, using the first imaging device and the second imaging device, a plurality of target positions of the plurality of targets; and   calibrating the one or more sensors based at least in part on the plurality of target positions.